A Multi-Dimensional LiDAR Method for Rural Building Extraction #WorldResearchAwards
Introduction Research on building extraction from airborne point clouds has been widely explored; however, rural environments present unique challenges due to the close interweaving of buildings and vegetation with similar height characteristics. These complexities often reduce the effectiveness of conventional urban-oriented methods. This research focuses on a representative rural region in China to address these limitations, proposing an adaptive and robust building classification framework tailored to complex rural landscapes. The study emphasizes improving accuracy, reducing redundancy, and enhancing practical applicability for real-world rural building data extraction. Terrain-Adaptive Ground Point Extraction The proposed methodology begins with terrain recognition through dynamic multi-level grid size determination based on slope analysis . By accurately distinguishing terrain types, differentiated filtering parameters are applied to each terrain category. This adaptive strat...